As state and local agencies consider the importance of compute location, it’s wise not to conflate fast and smart. City IT decision-makers must be thoughtful about when to use edge computing over traditional infrastructure.
In cases where edge computing is indeed necessary, cities must ensure they maximize the long-term value of those deployments by making them scalable and considering multiple use case scenarios.
When Edge Computing Is Essential
Edge computing offers incredible benefits on multiple fronts. Because it is processed locally rather than relayed between servers, it can reduce the time needed to transmit data. This means less overall network congestion and lower volumes of sensitive data transmitted across networks.
Still, these benefits alone do not offer a rationale for moving servers to the edge. There are other, more practical ways for state and local agencies to optimize existing IT infrastructure. Today, edge computing’s greatest value is for use cases that require the near-instantaneous processing of data that results in an immediate action. Its deployment should be reserved for those instances.
For example, traffic management systems rely on edge computing to adjust traffic signals in response to real-time conditions so emergency vehicles can pass through intersections without delay. The compute typically happens directly onboard the vehicle and the traffic light controller. Another use case for edge computing might be a school surveillance system that can detect suspicious behavior and trigger an immediate alert to emergency responders to protect staff and students.
These powerful, potentially lifesaving applications require edge computing because the systems must be not only smart to fulfill their intended function but also lightning fast.
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When Edge Computing Is Optional
There are many smart use cases that don’t require data processing in a millisecond; for instance, using cameras to take inventory of street signs.
In this hypothetical example, the feeds can be sent to a central server and processed to identify damaged or crooked street signs, which in turn triggers work orders. A crooked street sign will need to be fixed before it breaks, but the action doesn’t have to happen within seconds.
Consider another example, this one not hypothetical: In Little Rock, Ark., officials analyze municipal data about crime, vacant structures and a multitude of other factors to glean insights that help them solve problems. For instance, if data reveals that an area with a high concentration of vacant structures overlaps with a known food desert, they might prioritize the repurposing of that space as a grocery store.
Another common example of smart city technology in action is the use of digital twins. These virtual replicas of physical entities let city planners simulate scenarios based on real-world data. For instance, a digital twin could model the impact of a new shopping mall on local traffic patterns, helping planners anticipate and mitigate issues before they arise.
While digital twins don’t necessarily require edge computing, they rely heavily on data collection, artificial intelligence and advanced computing power, all of which are areas where edge computing can eventually play a supporting role.
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Balancing Real-Time Needs with Future Requirements
Edge computing has inherent challenges. It requires weather-resistant equipment, reliable power sources and robust physical access controls. Deployment can be complex, especially among smaller cities and towns that lack immediate access to technical expertise.
This is not to caution against edge computing. It’s the best solution when it comes to so many of the real-time use cases that make cities smarter and citizens safer. And ultimately, rapidly increasing data volumes generated by Internet of Things devices — and the need to process that data — will force more IT infrastructure toward the edge out of necessity for managing workloads.
But it is deeply important to have a strong understanding of which use cases require edge computing. It is equally important to take a highly strategic approach to implementation when edge computing is necessary. Edge servers and their connected endpoints can deliver multiple benefits if you plan for long-term flexibility, scalability, security and support, rather than jumping in just to satisfy an immediate need.
Use edge computing where it is the most practical solution for real-time digital services, but make sure you plan for scalability and future use cases.
